Hunch’s Recommendation Engine Goes Local

Hunch has launched what its co-founder, Chris Dixon, calls an alpha version of a new local recommendation engine. You can access it at hunch.com/local.

It’s not to be confused with Hunch’s existing Local category on the main Hunch.com site, and no one would confuse the two, anyway. The new Hunch Local is map-based (using Google Maps) and offers recommended businesses in your local area in a small window to the right of the map.

(click for larger version)

Hunch Local, like Hunch itself, works best when the service knows more about you. It relies on the your social connections — the ones it knows about — to make business recommendations that it thinks you might like. Business listings are often linked to profile pages on Yelp or Foursquare for more information. (It also works better in larger metropolitan areas where there are more Hunch users and more local businesses, meaning my Eastern Washington experience shown above is not the same as what someone in Seattle would get.)

One of the keys to the service is a simple question that appears with each business listing: “Do you like this?” As users supply their Yes/No answers, Hunch can do a better job of customizing recommendations in the future. Dixon explained how it all works together to TechCrunch:

It starts out looking at what your Facebook, Twitter, Foursquare friends like, and then gets smarter over time as people give feedback.

As I wrote last week, Hunch is planning to announce new partnerships soon that will involve Hunch’s recommendation engine being used to personalize other sites. When you look at this Hunch Local service, you can see pretty quickly how Hunch’s technology and knowledge could be applied in the local search/discovery space.

Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.

About The Author

Matt McGee joined Third Door Media as a writer/reporter/editor in September 2008. He served as Editor-In-Chief from January 2013 until his departure in July 2017. He can be found on Twitter at @MattMcGee.